Apparently Gaia identifiers will be added to the NASA archive in the near future, so it should hopefully be possible to fill in the missing TYC identifiers. At the moment it would not be possible to combine this with the Gaia results as the TYC identifiers are not exposed via the API, so the script would end up generating duplicate stars.

If you're using Celestia 1.6.1 then it will not work because I'm using the units syntax that unfortunately never made it into a released version of Celestia. The main reason is because it is a lot more convenient than using Celestia's defaults which tend to work best with our rather wide-spaced solar system and not so well once you start dealing with planetary orbital periods of a few days.

Either you'd need to compile Celestia from the SVN repository yourself (slightly annoying on Windows because qt4 and the latest Microsoft compiler don't seem to get along particularly well), or find someone else who's built it and has the binaries.

Either you'd need to compile Celestia from the SVN repository yourself (slightly annoying on Windows because qt4 and the latest Microsoft compiler don't seem to get along particularly well), or find someone else who's built it and has the binaries.

Maybe someone who has it can post it somewhere where only registered members can download it?

_________________If we all did the things we are capable of doing we would literally astound ourselves.Thomas Edison

The recent TRAPPIST-1 results have motivated me to do several updates to the scripts. In particular, the version currently on my GitHub is a mess, the logic for fixing holes in the data and doing the various processing is all mixed up with the parsing and outputting. Or to put it another way, the parser and the output know far too much astrophysics, and the stars and planets don't know any. This makes it rather tricky to add new features as there is no particularly good place to hook them in.

Over the weekend I extracted the astrophysics logic and gap filling into their own classes, which now gives a clear place to put features that fill in gaps in the data (e.g. mass-radius relationships, orientation of orbits, etc.) and hopefully will not be too difficult to extend for things like multiple star systems. I've also decided to go with Python 3 for now since I'm no longer using Forecaster, I may look into backporting to Python 2.7 when done but I no longer consider this a priority. I'm still using the mass-radius relationship from Chen & Kipping (2017) but I've written a "fast and nasty integrator" to do the estimation, as the Monte-Carlo approach is both too slow and as it is random-number based, gives different results each time you run it.

I've also implemented mass thresholds for rock and ice planets, plus tidal spindown models with pseudosynchronous rotation (for gas giants) and spin-orbit resonances (for rock/ice planets). Encouragingly, the code that predicts which spin-orbit resonance the planet will end up in gets the 3:2 state for Mercury correct.

A couple of examples: first, the HD 38529 system - the inner gas giant is in an eccentric orbit and has reached a pseudosynchronous rotation state, while the outer giant has not been slowed down, and has a rotation derived from the solar system mass-equatorial velocity relationship (observations of Beta Pictoris b and 2M1207b seem to indicate it is fairly consistent out to superjovian masses).

Tidying up existing features, e.g. check I didn't break anything regarding accurate simulation of transits, ensure all references are output in the ssc/stc file headers, not just as comments in the code

Use orientation information from other planets in the system to stop systems of transiting and non-transiting planets being wildly misaligned

Further characteristation of planets based on temperature, mass, rotation, etc.

I'm still using the mass-radius relationship from Chen & Kipping (2017)

Perhaps it would be a good strategy to relate or unify the used mass-radius relationship and the mass-luminosity (ML) relationship that Dawoon and myself have used in our Lensing framework code/papers. The ML relation holds over a huge range of masses from stars to galaxy clusters! While the paper by Torres et al (2009) refers mainly to stars, the recent paper by Bahcall and Kulier(2014) has become quickly a standard reference for galaxies and galaxy clusters...

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